code: def test_dkwm_argument_validity_checking(self, dtype):
      rng = np.random.RandomState(seed=0)
      samples = rng.uniform(
          low=[0.0, 1.0], high=[1.0, 2.0], size=(2500, 1, 2)
      ).astype(dtype=dtype)
  
      # Test that the test library complains if the given samples fall
      # outside the purported bounds.
      with self.assertRaisesOpError(
          "maximum value exceeds expectations"
      ):
          self.evaluate(
              st.true_mean_confidence_interval_by_dkwm(
                  samples, [[0.0, 1.0]], [[0.5, 1.5]], error_rate=0.5
              )
          )
      with self.assertRaisesOpError(
          "minimum value falls below expectations"
      ):
          self.evaluate(
              st.true_mean_confidence_interval_by_dkwm(
                  samples, [[0.5, 1.5]], [[1.0, 2.0]], error_rate=0.5
              )
          )
  
      # But doesn't complain if they don't.
      op = st.true_mean_confidence_interval_by_dkwm(
          samples, [[0.0, 1.0]], [[1.0, 2.0]], error_rate=0.5
      )
      _ = self.evaluate(op)
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 19 for calling the StatisticalTestingTest obj's underlying member method code with example usage: obj.test_dkwm_argument_validity_checking(dtype) without return types